• DocumentCode
    25713
  • Title

    Low-Power Wireless ECG Acquisition and Classification System for Body Sensor Networks

  • Author

    Shuenn-Yuh Lee ; Jia-Hua Hong ; Cheng-Han Hsieh ; Ming-Chun Liang ; Shih-Yu Chang Chien ; Kuang-Hao Lin

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • Volume
    19
  • Issue
    1
  • fYear
    2015
  • fDate
    Jan. 2015
  • Firstpage
    236
  • Lastpage
    246
  • Abstract
    A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.
  • Keywords
    CMOS integrated circuits; amplitude shift keying; biomedical electronics; biomedical telemetry; body sensor networks; digital signal processing chips; electrocardiography; low-power electronics; medical signal processing; signal classification; wavelet transforms; DSP; TSMC 0.18-μm standard CMOS process; beat detection; body sensor networks; body-end circuits; cardiologists; chips; classification system; diagnosis control; digital signal processor; digitization; electrocardiogram classification; high-pass sigma delta modulator-based biosignal processor; low-power biosignal acquisition; low-power super-regenerative on-off keying transceiver; low-power wireless ECG acquisition; personal computers; power 586.5 muW; power consumption; power supply; radio frequency receiver; receiving-end circuits; short-range wireless transmission; signal acquisition; size 0.18 mum; smartphones; time 80 d; transmitter circuits; wavelet transform-based digital signal processing circuit; zinc-air batteries; Digital signal processing; Electrocardiography; Modulation; Monitoring; Power demand; Transceivers; Wireless communication; Body sensor network (BSN); electrocardiogram (ECG); high-pass sigma-delta modulator (HPSDM); super-regenerative on–off keying (OOK) transceiver; wavelet transform;
  • fLanguage
    English
  • Journal_Title
    Biomedical and Health Informatics, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    2168-2194
  • Type

    jour

  • DOI
    10.1109/JBHI.2014.2310354
  • Filename
    6762857